We describe an MRI image synthesis algorithm capable of synthesizing full-head T2w images and FLAIR images.
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Our algorithm, REPLICA, is a supervised method and learns the nonlinear intensity mappings for synthesis using innovative features and a multi-resolution design.
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We show significant improvement in synthetic image quality over state-of-the-art image synthesis algorithms.
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We also demonstrate that image analysis tasks like segmentation perform similarly for real and REPLICA-generated synthetic images.
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REPLICA is computationally very fast and can be easily used as a preprocessing tool before further image analysis.
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